Fragment and torsion biasing algorithms for construction of small organic molecules in proteins using DOCK.

The computational construction of small organic molecules (de novo design), directly in a protein binding site, is an effective means for generating novel ligands tailored to fit the pocket environment. In this work, we present two new methods, which aim to improve de novo design outcomes using (1) biasing algorithms to prioritize selection and/or acceptance of fragments and torsions during growth, and (2) parallel-based clustering and pruning algorithms to remove duplicate molecules as candidate fragment are added. Large-scale testing encompassing thousands of simulations were employed to interrogate the methods in terms of multiple metrics which include numbers of duplicate molecules generated, pairwise-similarity, focused library reconstruction rates, fragment and torsion frequencies, fragment and torsion rank scores, interaction energy and drug-likeness scores, and 3D pose comparisons. The biasing algorithms, particularly those that include fragment and torsion components simultaneously, led to molecules that more closely mimicked the distributions of fragments and torsions found in drug-like libraries. The new parallel-based clustering and pruning algorithms, compared with the existing serial approach, also led to larger ensembles comprised of topologically unique molecules with much greater efficiency by removing redundant growth paths.

Descriptor-Driven de Novo Design Algorithms for DOCK6 Using RDKit.

Structure-based methods that employ principles of de novo design can be used to construct small organic molecules from scratch using pre-existing fragment libraries to sample chemical space and are an important class of computational algorithms for drug-lead discovery. Here, we present a powerful new design method for DOCK6 that employs a Descriptor-Driven De Novo strategy (termed D3N) in which user-defined cheminformatics descriptors (and their target ranges) are calculated at each layer of growth using the open-source toolkit RDKit. The objective is to tailor ligand growth toward desirable regions of chemical space. The approach was extensively validated through: (1) comparison of cheminformatics descriptors computed using the new DOCK6/RDKit interface versus the standard Python/RDKit installation, (2) examination of descriptor distributions generated using D3N growth under different conditions (target ranges and environments), and (3) construction of ligands with very tight (pinpoint) descriptor ranges using clinically relevant compounds as a reference. Our testing confirms that the new DOCK6/RDKit integration is robust, showcases how the new D3N routines can be used to direct sampling around user-defined chemical spaces, and highlights the utility of on-the-fly descriptor calculations for ligand design to important drug targets.

Neutral ceramidase-active site inhibitor chemotypes and binding modes.

Ceramides impact a diverse array of biological functions and have been implicated in disease pathogenesis. The enzyme neutral ceramidase (nCDase) is a zinc-containing hydrolase and mediates the metabolism of ceramide to sphingosine (Sph), both in cells and in the intestinal lumen. nCDase inhibitors based on substrate mimetics, for example C6-urea ceramide, have limited potency, aqueous solubility, and micelle-free fraction. To identify non-ceramide mimetic nCDase inhibitors, hit compounds from an HTS campaign were evaluated in biochemical, cell based and in silico modeling approaches. A majority of small molecule nCDase inhibitors contained pharmacophores capable of zinc interaction but retained specificity for nCDase over zinc-containing acid and alkaline ceramidases, as well as matrix metalloprotease-3 and histone deacetylase-1. nCDase inhibitors were refined by SAR, were shown to be substrate competitive and were active in cellular assays. nCDase inhibitor compounds were modeled by in silico DOCK screening and by molecular simulation. Modeling data supports zinc interaction and a similar compound binding pose with ceramide. nCDase inhibitors were identified with notably improved activity and solubility in comparison with the reference lipid-mimetic C6-urea ceramide.

A molecular evolution algorithm for ligand design in DOCK.

As a complement to virtual screening, de novo design of small molecules is an alternative approach for identifying potential drug candidates. Here, we present a new 3D genetic algorithm to evolve molecules through breeding, mutation, fitness pressure, and selection. The method, termed DOCK_GA, builds upon and leverages powerful sampling, scoring, and searching routines previously implemented into DOCK6. Three primary experiments were used during development: Single-molecule evolution evaluated three selection methods (elitism, tournament, and roulette), in four clinically relevant systems, in terms of mutation type and crossover success, chemical properties, ensemble diversity, and fitness convergence, among others. Large scale benchmarking assessed performance across 651 different protein-ligand systems. Ensemble-based evolution demonstrated using multiple inhibitors simultaneously to seed growth in a SARS-CoV-2 target. Key takeaways include: (1) The algorithm is robust as demonstrated by the successful evolution of molecules across a large diverse dataset. (2) Users have flexibility with regards to parent input, selection method, fitness function, and molecular descriptors. (3) The program is straightforward to run and only requires a single executable and input file at run-time. (4) The elitism selection method yields more tightly clustered molecules in terms of 2D/3D similarity, with more favorable fitness, followed by tournament and roulette.

Free Energy Landscapes from SARS-CoV-2 Spike Glycoprotein Simulations Suggest that RBD Opening Can Be Modulated via Interactions in an Allosteric Pocket.

The SARS-CoV-2 coronavirus is an enveloped, positive-sense single-stranded RNA virus that is responsible for the COVID-19 pandemic. The spike is a class I viral fusion glycoprotein that extends from the viral surface and is responsible for viral entry into the host cell and is the primary target of neutralizing antibodies. The receptor binding domain (RBD) of the spike samples multiple conformations in a compromise between evading immune recognition and searching for the host-cell surface receptor. Using atomistic simulations of the glycosylated wild-type spike in the closed and 1-up RBD conformations, we map the free energy landscape for RBD opening and identify interactions in an allosteric pocket that influence RBD dynamics. The results provide an explanation for experimental observation of increased antibody binding for a clinical variant with a substitution in this pocket. Our results also suggest the possibility of allosteric targeting of the RBD equilibrium to favor open states via binding of small molecules to the hinge pocket. In addition to potential value as experimental probes to quantify RBD conformational heterogeneity, small molecules that modulate the RBD equilibrium could help explore the relationship between RBD opening and S1 shedding.

Identification of Zika Virus Inhibitors Using Homology Modeling and Similarity-Based Screening to Target Glycoprotein E.

The World Health Organization has designated Zika virus (ZIKV) as a dangerous, mosquito-borne pathogen that can cause severe developmental defects. The primary goal of this work was identification of small molecules as potential ZIKV inhibitors that target the viral envelope glycoprotein (ZIKV E) involved in membrane fusion and viral entry. A homology model of ZIKV E containing the small molecule ß-octyl glucoside (BOG) was constructed, on the basis of an analogous X-ray structure from dengue virus, and >4 million commercially available compounds were computationally screened using the program DOCK6. A key feature of the screen involved the use of similarity-based scoring to identify inhibitor candidates that make similar interaction energy patterns (molecular footprints) as the BOG reference. Fifty-three prioritized compounds underwent experimental testing using cytotoxicity, cell viability, and tissue culture infectious dose 50% (TCID50) assays. Encouragingly, relative to a known control (NITD008), six compounds were active in both the cell viability assay and the TCID50 infectivity assay, and they showed activity in a third caspase activity assay. In particular, compounds 8 and 15 (tested at 25 µM) and compound 43 (tested at 10 µM) appeared to provide significant protection to infected cells, indicative of anti-ZIKV activity. Overall, the study highlights how similarity-based scoring can be leveraged to computationally identify potential ZIKV E inhibitors that mimic a known reference (in this case BOG), and the experimentally verified hits provide a strong starting point for further refinement and optimization efforts.

Identification of Ebola Virus Inhibitors Targeting GP2 Using Principles of Molecular Mimicry.

A key step in the Ebola virus (EBOV) replication cycle involves conformational changes in viral glycoprotein 2 (GP2) which facilitate host-viral membrane fusion and subsequent release of the viral genome. Ebola GP2 plays a critical role in virus entry and has similarities in mechanism and structure to the HIV gp41 protein for which inhibitors have been successfully developed. In this work, a putative binding pocket for the C-terminal heptad repeat in the N-terminal heptad repeat trimer was targeted for identification of small molecules that arrest EBOV-host membrane fusion. Two computational structure-based virtual screens of ∼1.7 M compounds were performed (DOCK program) against a GP2 five-helix bundle, resulting in 165 commercially available compounds purchased for experimental testing. Based on assessment of inhibitory activity, cytotoxicity, and target specificity, four promising candidates emerged with 50% inhibitory concentration values in the 3 to 26 µM range. Molecular dynamics simulations of the two most potent candidates in their DOCK-predicted binding poses indicate that the majority of favorable interactions involve seven highly conserved residues that can be used to guide further inhibitor development and refinement targeting EBOV.IMPORTANCE The most recent Ebola virus disease outbreak, from 2014 to 2016, resulted in approximately 28,000 individuals becoming infected, which led to over 12,000 causalities worldwide. The particularly high pathogenicity of the virus makes paramount the identification and development of promising lead compounds to serve as inhibitors of Ebola infection. To limit viral load, the virus-host membrane fusion event can be targeted through the inhibition of the class I fusion glycoprotein of Ebolavirus In the current work, several promising small-molecule inhibitors that target the glycoprotein GP2 were identified through systematic application of structure-based computational and experimental drug design procedures.

Identification of Fatty Acid Binding Protein 5 Inhibitors Through Similarity-Based Screening.

Fatty acid binding protein 5 (FABP5) is a promising target for development of inhibitors to help control pain and inflammation. In this work, computer-based docking (DOCK6 program) was employed to screen ∼2 M commercially available compounds to FABP5 based on an X-ray structure complexed with the small molecule inhibitor SBFI-26 previously identified by our group (also through virtual screening). The goal was discovery of additional chemotypes. The screen resulted in the purchase of 78 candidates, which led to the identification of a new inhibitor scaffold (STK-0) with micromolar affinity and apparent selectivity for FABP5 over FABP3. A second similarity-based screen resulted in three additional hits (STK-15, STK-21, STK-22) from which preliminary SAR could be derived. Notably, STK-15 showed comparable activity to the SBFI-26 reference under the same assay conditions (1.40 vs 0.86 µM). Additional molecular dynamics simulations, free energy calculations, and structural analysis (starting from DOCK-generated poses) revealed that R enantiomers (dihydropyrrole scaffold) of STK-15 and STK-22 have a more optimal composition of functional groups to facilitate additional H-bonds with Arg109 of FABP5. This observation suggests enantiomerically pure compounds could show enhanced activity. Overall, our study highlights the utility of using similarity-based screening methods to discover new inhibitor chemotypes, and the identified FABP5 hits provide a strong starting point for future efforts geared to improve activity.

Identification of a Water-Coordinating HER2 Inhibitor by Virtual Screening Using Similarity-Based Scoring.

Human epidermal growth factor receptor 2 (HER2) is a validated breast cancer drug target for small molecule inhibitors that target the ATP-binding pocket of the kinase domain. In this work, a large-scale virtual screen was performed to a novel homology model of HER2, in a hypothesized "fully active" state, that considered water-mediated interactions during the prioritization of compounds for experimental testing. This screen led to the identification of a new inhibitor with micro molar affinity and potency ( Kd = 7.0 µM, IC50 = 4.6 µM). Accompanying molecular dynamics simulations showed that inhibitor binding likely involves water coordination through an important water-mediated network previously identified in our laboratory. The predicted binding geometry also showed a remarkable overlap with the crystallographic poses for two previously reported inhibitors of the related Chk1 kinase. Concurrent with the HER2 studies, we developed formalized computational protocols that leverage solvated footprints (per-residue interaction maps that include bridging waters) to identify ligands that can "coordinate" or "displace" key binding site waters. Proof-of-concept screens targeting HIVPR and PARP1 demonstrate that molecules with high footprint overlap can be effectively identified in terms of their coordination or displacement patterns relative to a known reference. Overall, the procedures developed as a result of this study should be useful for researchers targeting HER2 and, more generally, for any protein in which the identification of compounds that exploit binding site waters is desirable.

The Antinociceptive Agent SBFI-26 Binds to Anandamide Transporters FABP5 and FABP7 at Two Different Sites.

Human FABP5 and FABP7 are intracellular endocannabinoid transporters. SBFI-26 is an α-truxillic acid 1-naphthyl monoester that competitively inhibits the activities of FABP5 and FABP7 and produces antinociceptive and anti-inflammatory effects in mice. The synthesis of SBFI-26 yields several stereoisomers, and it is not known how the inhibitor binds the transporters. Here we report co-crystal structures of SBFI-26 in complex with human FABP5 and FABP7 at 2.2 and 1.9 Å resolution, respectively. We found that only (S)-SBFI-26 was present in the crystal structures. The inhibitor largely mimics the fatty acid binding pattern, but it also has several unique interactions. Notably, the FABP7 complex corroborates key aspects of the ligand binding pose at the canonical site previously predicted by virtual screening. In FABP5, SBFI-26 was unexpectedly found to bind at the substrate entry portal region in addition to binding at the canonical ligand-binding pocket. Our structural and binding energy analyses indicate that both R and S forms appear to bind the transporter equally well. We suggest that the S enantiomer observed in the crystal structures may be a result of the crystallization process selectively incorporating the (S)-SBFI-26-FABP complexes into the growing lattice, or that the S enantiomer may bind to the portal site more rapidly than to the canonical site, leading to an increased local concentration of the S enantiomer for binding to the canonical site. Our work reveals two binding poses of SBFI-26 in its target transporters. This knowledge will guide the development of more potent FABP inhibitors based upon the SBFI-26 scaffold.

Fatty-acid-binding protein inhibition produces analgesic effects through peripheral and central mechanisms.

Background Fatty-acid-binding proteins (FABPs) are intracellular carriers for endocannabinoids, N-acylethanolamines, and related lipids. Previous work indicates that systemically administered FABP5 inhibitors produce analgesia in models of inflammatory pain. It is currently not known whether FABP inhibitors exert their effects through peripheral or central mechanisms. Here, we examined FABP5 distribution in dorsal root ganglia and spinal cord and examined the analgesic effects of peripherally and centrally administered FABP5 inhibitors. Results Immunofluorescence revealed robust expression of FABP5 in lumbar dorsal root ganglia. FABP5 was distributed in peptidergic calcitonin gene-related peptide-expressing dorsal root ganglia and non-peptidergic isolectin B4-expressing dorsal root ganglia. In addition, the majority of dorsal root ganglia expressing FABP5 also expressed transient receptor potential vanilloid 1 (TRPV1) and peripherin, a marker of nociceptive fibers. Intraplantar administration of FABP5 inhibitors reduced thermal and mechanical hyperalgesia in the complete Freund's adjuvant model of chronic inflammatory pain. In contrast to its robust expression in dorsal root ganglia, FABP5 was sparsely distributed in the lumbar spinal cord and intrathecal administration of FABP inhibitor did not confer analgesic effects. Administration of FABP inhibitor via the intracerebroventricular (i.c.v.) route reduced thermal hyperalgesia. Antagonists of peroxisome proliferator-activated receptor alpha blocked the analgesic effects of peripherally and i.c.v. administered FABP inhibitor while antagonism of cannabinoid receptor 1 blocked the effects of peripheral FABP inhibition and a TRPV1 antagonist blocked the effects of i.c.v. administered inhibitor. Although FABP5 and TRPV1 were co-expressed in the periaqueductal gray region of the brain, which is known to modulate pain, knockdown of FABP5 in the periaqueductal gray using adeno-associated viruses and pharmacological FABP5 inhibition did not produce analgesic effects. Conclusions This study demonstrates that FABP5 is highly expressed in nociceptive dorsal root ganglia neurons and FABP inhibitors exert peripheral and supraspinal analgesic effects. This indicates that peripherally restricted FABP inhibitors may serve as a new class of analgesic and anti-inflammatory agents.

Customizable de novo design strategies for DOCK: Application to HIVgp41 and other therapeutic targets.

De novo design can be used to explore vast areas of chemical space in computational lead discovery. As a complement to virtual screening, from-scratch construction of molecules is not limited to compounds in pre-existing vendor catalogs. Here, we present an iterative fragment growth method, integrated into the program DOCK, in which new molecules are built using rules for allowable connections based on known molecules. The method leverages DOCK's advanced scoring and pruning approaches and users can define very specific criteria in terms of properties or features to customize growth toward a particular region of chemical space. The code was validated using three increasingly difficult classes of calculations: (1) Rebuilding known X-ray ligands taken from 663 complexes using only their component parts (focused libraries), (2) construction of new ligands in 57 drug target sites using a library derived from ∼13M drug-like compounds (generic libraries), and (3) application to a challenging protein-protein interface on the viral drug target HIVgp41. The computational testing confirms that the de novo DOCK routines are robust and working as envisioned, and the compelling results highlight the potential utility for designing new molecules against a wide variety of important protein targets. © 2017 Wiley Periodicals, Inc.

Structure-based identification of inhibitors targeting obstruction of the HIVgp41 N-heptad repeat trimer.

The viral protein HIVgp41 is an attractive and validated drug target that proceeds through a sequence of conformational changes crucial for membrane fusion, which facilitates viral entry. Prior work has identified inhibitors that interfere with the formation of a required six-helix bundle, composed of trimeric C-heptad (CHR) and N-heptad (NHR) repeat elements, through blocking association of an outer CHR helix or obstructing formation of the inner NHR trimer itself. In this work, we employed similarity-based scoring to identify and experimentally characterize 113 compounds, related to 2 small-molecule inhibitors recently reported by Allen et al. (Bioorg. Med. Chem Lett.2015, 25 2853-59), proposed to act via the NHR trimer obstruction mechanism. The compounds were first tested in an HIV cell-cell fusion assay with the most promising evaluated in a second, more biologically relevant viral entry assay. Of the candidates, compound #11 emerged as the most promising hit (IC50=37.81µM), as a result of exhibiting activity in both assays with low cytotoxicity, as was similarly seen with the known control peptide inhibitor C34. The compound also showed no inhibition of VSV-G pseudotyped HIV entry compared to a control inhibitor suggesting it was specific for HIVgp41. Molecular dynamics simulations showed the predicted DOCK pose of #11 interacts with HIVgp41 in an energetic fashion (per-residue footprints) similar to the four native NHR residues (IQLT) which candidate inhibitors were intended to mimic.

Identification of small molecule inhibitors of botulinum neurotoxin serotype E via footprint similarity.

Botulinum neurotoxins (BoNT) are among the most poisonous substances known, and of the 7 serotypes (A-G) identified thus far at least 4 can cause death in humans. The goal of this work was identification of inhibitors that specifically target the light chain catalytic site of the highly pathogenic but lesser-studied E serotype (BoNT/E). Large-scale computational screening, employing the program DOCK, was used to perform atomic-level docking of 1.4 million small molecules to prioritize those making favorable interactions with the BoNT/E site. In particular, 'footprint similarity' (FPS) scoring was used to identify compounds that could potentially mimic features on the known substrate tetrapeptide RIME. Among 92 compounds purchased and experimentally tested, compound C562-1101 emerged as the most promising hit with an apparent IC50 value three-fold more potent than that of the first reported BoNT/E small molecule inhibitor NSC-77053. Additional analysis showed the predicted binding pose of C562-1101 was geometrically and energetically stable over an ensemble of structures generated by molecular dynamic simulations and that many of the intended interactions seen with RIME were maintained. Several analogs were also computationally designed and predicted to have further molecular mimicry thereby demonstrating the potential utility of footprint-based scoring protocols to help guide hit refinement.

DOCK 6: Impact of new features and current docking performance.

This manuscript presents the latest algorithmic and methodological developments to the structure-based design program DOCK 6.7 focused on an updated internal energy function, new anchor selection control, enhanced minimization options, a footprint similarity scoring function, a symmetry-corrected root-mean-square deviation algorithm, a database filter, and docking forensic tools. An important strategy during development involved use of three orthogonal metrics for assessment and validation: pose reproduction over a large database of 1043 protein-ligand complexes (SB2012 test set), cross-docking to 24 drug-target protein families, and database enrichment using large active and decoy datasets (Directory of Useful Decoys [DUD]-E test set) for five important proteins including HIV protease and IGF-1R. Relative to earlier versions, a key outcome of the work is a significant increase in pose reproduction success in going from DOCK 4.0.2 (51.4%) → 5.4 (65.2%) → 6.7 (73.3%) as a result of significant decreases in failure arising from both sampling 24.1% → 13.6% → 9.1% and scoring 24.4% → 21.1% → 17.5%. Companion cross-docking and enrichment studies with the new version highlight other strengths and remaining areas for improvement, especially for systems containing metal ions. The source code for DOCK 6.7 is available for download and free for academic users at http://dock.compbio.ucsf.edu/.

Small molecule inhibitors of HIVgp41 N-heptad repeat trimer formation.

Identification of mechanistically novel anti-HIV fusion inhibitors was accomplished using a computer-aided structure-based design approach with the goal of blocking the formation of the N-heptad repeat (NHR) trimer of the viral protein gp41. A virtual screening strategy that included per-residue interaction patterns (footprints) was employed to identify small molecules compatible with putative binding pockets at the internal interface of the NHR helices at the core native viral six-helix bundle. From a screen of ∼2.8 million compounds using the DOCK program, 120 with favorable energetic and footprint overlap characteristics were purchased and experimentally tested leading to two compounds with favorable cell-cell fusion (IC50) and cytotoxicity profiles. Importantly, both hits were identified on the basis of scores containing footprint overlap terms and would not have been identified using the standard DOCK energy function alone. To our knowledge, these compounds represent the first reported small molecules that inhibit viral entry via the proposed NHR-trimer obstruction mechanism.

Computer-aided identification, synthesis, and biological evaluation of novel inhibitors for botulinum neurotoxin serotype A.

Botulinum neurotoxins (BoNTs) are among the most potent biological toxin known to humans, and are classified as Category A bioterrorism agents by the Centers for Disease Control and prevention (CDC). There are seven known BoNT serotypes (A-G) which have been thus far identified in literature. BoNTs have been shown to block neurotransmitter release by cleaving proteins of the soluble NSF attachment protein receptor (SNARE) complex. Disruption of the SNARE complex precludes motor neuron failure which ultimately results in flaccid paralysis in humans and animals. Currently, there are no effective therapeutic treatments against the neurotoxin light chain (LC) after translocation into the cytosols of motor neurons. In this work, high-throughput in silico screening was employed to screen a library of commercially available compounds from ZINC database against BoNT/A-LC. Among the hit compounds from the in silico screening, two lead compounds were identified and found to have potent inhibitory activity against BoNT/A-LC in vitro, as well as in Neuro-2a cells. A few analogs of the lead compounds were synthesized and their potency examined. One of these analogs showed an enhanced activity than the lead compounds.

Implementation of the Hungarian algorithm to account for ligand symmetry and similarity in structure-based design.

False negative docking outcomes for highly symmetric molecules are a barrier to the accurate evaluation of docking programs, scoring functions, and protocols. This work describes an implementation of a symmetry-corrected root-mean-square deviation (RMSD) method into the program DOCK based on the Hungarian algorithm for solving the minimum assignment problem, which dynamically assigns atom correspondence in molecules with symmetry. The algorithm adds only a trivial amount of computation time to the RMSD calculations and is shown to increase the reported overall docking success rate by approximately 5% when tested over 1043 receptor-ligand systems. For some families of protein systems the results are even more dramatic, with success rate increases up to 16.7%. Several additional applications of the method are also presented including as a pairwise similarity metric to compare molecules during de novo design, as a scoring function to rank-order virtual screening results, and for the analysis of trajectories from molecular dynamics simulation. The new method, including source code, is available to registered users of DOCK6 ( http://dock.compbio.ucsf.edu ).

Strategies for lead discovery: application of footprint similarity targeting HIVgp41.

A highly-conserved binding pocket on HIVgp41 is an important target for development of anti-viral inhibitors. Holden et al. (Bioorg. Med. Chem. Lett.2012, 22, 3011) recently reported 7 experimentally-verified leads identified through a computational screen to the gp41 pocket in conjunction with a new DOCK scoring method (termed FPS scoring) developed in our laboratory. The method employs molecular footprints based on per-residue van der Waals interactions, electrostatic interactions, or the sum. In this work, we critically examine the gp41 screening results, prioritized using different scoring methods, in terms of two main criteria: (1) ligand pose properties which include footprint and energy score decompositions, MW, number of rotatable bonds, ligand efficiency, formal charge, and volume overlap, and (2) ligand pose stability which includes footprint stability (changes in footprint overlap) and rmsd stability (changes in geometry). Relative to standard DOCK scoring, pose property analyses demonstrate how FPS scoring can be used to identify ligands that mimic a known reference (derived here from the native gp41 substrate), while pose stability analyses demonstrate how FPS scoring can be used to enrich for compounds with greater overall stability during molecular dynamics (MD) simulations. Compellingly, of the 115 compounds tested experimentally, the 7 active compounds, as a group, more closely mimic the footprints made by the reference and show greater MD stability compared to the inactive group. Extensive studies using 116 protein-ligand complexes as controls reveal that ligands in their crystallographic binding pose also maintain higher FPS scores and smaller rmsds than do accompanying decoys, confirming that native poses are indeed 'stable' under the same conditions and that monitoring FPS variability during compound prioritization is likely to be beneficial. Overall, the results suggest the new scoring method will complement current virtual screening approaches for both the identification (FPS-ranking) and prioritization (FPS-stability) of target-compatible molecules in a quantitative and logical way.